A casual glance at a modern television broadcast highlights how electronic data presentations have become ubiquitous to everyday experiences. From broadcasts that graphically illustrate one statistic or trend over another to the ever competitive business presentations that provide consumers with up-to-the minute details and analysis of micro and macroeconomic news. Perhaps the most common experience is viewing linear graphs at the end of the day that depicts how the Dow Jones industrial averages have performed on a given day. Such data is often shown as a trend analysis where the overall performance has increased, decreased, and peaked or declined along a linear graph—over a short period of time. Oftentimes, particular market segments are analyzed, charted and displayed, whereas in other instances, individual corporations or other entities are presented and viewed for further analysis.
In all these visualization examples and others, although the actual data may be changing to update the particular graph of interest, the form or nature of the graph remains unchanging (e.g., a bar graph showing NBA scoring averages over time remains a bar graph form regardless if the averages have changed in some manner that might warrant another visualization). Thus, current visualization schemes do not have the ability to adjust the actual form over time even though another type or form of visualization for the respective data may be more appropriate at a given point in time. The following describes other current visualization techniques that suffer from static or rigid presentation capabilities.
In another example of a visualization technology, three dimensional (3D) visualizations may be shown in the form of a relief chart where data is represented as peaks and valleys over different portions of a three dimensional graph. These are powerful tools that allow one to view and more importantly analyze data. Such tools include many features such as viewpoints that enable users to view visualizations based upon pre-defined “viewpoints” which can be defined by users based upon terms of interest. These can also include viewing visualizations based on measurement of affect (emotion) and other evidence data. Other features include copying of networks, administrator modification of networks, and time query capabilities.
The 3D tool allows Boolean query results to be ranked in a document viewer according to their relevance to an initial query, where users can enter annotations in files and also query the annotations via a query tool. This also includes providing user interfaces for the query tool, font size control for a document viewer and visualizations functions such as “Right Click” query on selected text, and user specified ordering in a correlation tool. Streaming data feed visualizations can also be accommodated by the 3D tool that continuously updates dataset visualizations from a news feed or other type of incrementally updated textual source. This can include data sharing where document lists are exchanged and associated metadata with other information systems is collected. Interface aspects of the 3D tool allow user-defined source document retrieval to access source documents via a user provided executable, enabling users to define how documents should be accessed or pre-processed before being sent to the viewer. As noted previously however, the 3D tool although able to update changing data per a pre-defined visualization/output format, does not alter the static capabilities or form of the overall data output represented by the respective visualization.
Other visualization tools include information models that are flexible and powerful yet still statically coupled to a pre-defined visualization display. Information models are capable of tightly integrating disparate, multi-format (and multimedia) information and data—enabling concurrent analysis. Another model addresses security problems by assessing web sites automatically, incorporating Internet site harvesting, web page characterization, link visualization, and complete analysis functionality. Still yet another tool provides a graphical wall designed to help users more easily monitor and explore continually updating text sources such as news or other reports, through a high-resolution touch-screen interface. In yet another tool surveyed, data mining software has been developed for handling large volumes of information relevant to the scientific and business needs of life and chemical sciences industries. The associated mining methods provide visualization schemes for high-dimensional data, coupled with a suite of interactive tools to enable efficient data mining. The tool visualizations are applicable to many data types that allow integrated views of diverse information including unstructured text, numerical data, categorical information, and genomic sequences. In all these example systems, although data may change a pre-defined format display (e.g., cause a data mountain to grow or shrink, cause a linear graph to change peaks and valleys), the nature of the display itself remains unchanged and that may hinder efficient data analysis.